Estimation of difficult-to-measure process variables using neural networks - a comparison of simple MLP and RBF neural network properties

@article{Sliskovic2004EstimationOD,
  title={Estimation of difficult-to-measure process variables using neural networks - a comparison of simple MLP and RBF neural network properties},
  author={Drazen Sliskovic and E. K. Nyarko and Nedjeljko Peric},
  journal={Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No.04CH37521)},
  year={2004},
  volume={1},
  pages={387-390 Vol.1}
}
In this paper, two different artificial neural networks are tested and compared with regard to their application in the estimation of difficult-to-measure process variables. Two of the most commonly used neural networks, the MLP (multilayer perceptron) and RBF (radial basis function) neural networks, with simple structure and standard training methods are… CONTINUE READING